Import and process data

Learning

Model: Correct responses by age, trial, block number, and block condition

	correct_response_made
Predictors	Odds Ratios	CI
age scaled	1.2545	1.1664 – 1.3493
learning trial scaled	1.6632	1.6003 – 1.7286
reward condition1	1.6195	1.5376 – 1.7057
block number scaled	1.2588	1.1921 – 1.3293
age scaled × learning trial scaled	1.1124	1.0703 – 1.1561
age scaled × reward condition1	1.0722	1.0179 – 1.1294
learning trial scaled × reward condition1	1.1488	1.1150 – 1.1836
age scaled × block number scaled	0.9780	0.9258 – 1.0331
learning trial scaled × block number scaled	1.0684	1.0356 – 1.1022
reward condition1 × block number scaled	1.0580	1.0124 – 1.1057
age scaled × learning trial scaled × reward condition1	1.0462	1.0150 – 1.0784
(age scaled × learning trial scaled) × block number scaled	1.0065	0.9751 – 1.0389
(age scaled × reward condition1) × block number scaled	0.9897	0.9466 – 1.0347
(learning trial scaled × reward condition1) × block number scaled	1.0141	0.9845 – 1.0446
(age scaled × learning trial scaled × reward condition1) × block number scaled	1.0075	0.9775 – 1.0383
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.17
τ₁₁ _{subject_id.re1.learning_trial_scaled}	0.02
τ₁₁ _{subject_id.re1.reward_condition1}	0.07
τ₁₁ _{subject_id.re1.block_number_scaled}	0.08
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_reward_condition1}	0.00
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_block_number_scaled}	0.00
τ₁₁ _{subject_id.re1.reward_condition1_by_block_number_scaled}	0.04
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_reward_condition1_by_block_number_scaled}	0.00
ρ₀₁
ρ₀₁
ICC	0.05
N _{subject_id}	151
Observations	38352
Marginal R² / Conditional R²	0.146 / 0.188

Figure 2A: Correct response by block condition, stimulus repetition, and age group

Supplementary Figure: Correct response by block condition and block number

Figure 2B: Generalization by block condition, category repetition, age group

Model: Correct response to first appearance of each stimulus

	correct_response_made
Predictors	Odds Ratios	CI
age scaled	1.0630	1.0168 – 1.1112
category rep scaled	1.2479	1.1926 – 1.3057
reward condition1	1.7160	1.6298 – 1.8068
block number scaled	1.0946	1.0478 – 1.1435
age scaled × category rep scaled	1.0572	1.0101 – 1.1066
age scaled × reward condition1	1.0705	1.0166 – 1.1272
category rep scaled × reward condition1	1.3200	1.2616 – 1.3812
age scaled × block number scaled	1.0003	0.9572 – 1.0453
category rep scaled × block number scaled	1.0461	0.9999 – 1.0945
reward condition1 × block number scaled	1.0953	1.0484 – 1.1443
age scaled × category rep scaled × reward condition1	1.0753	1.0273 – 1.1255
(age scaled × category rep scaled) × block number scaled	1.0225	0.9768 – 1.0704
(age scaled × reward condition1) × block number scaled	1.0027	0.9594 – 1.0479
(category rep scaled × reward condition1) × block number scaled	1.0678	1.0206 – 1.1171
(age scaled × category rep scaled × reward condition1) × block number scaled	1.0283	0.9823 – 1.0764
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.01
τ₁₁ _{subject_id.re1.block_number_scaled}	0.01
τ₁₁ _{subject_id.re1.reward_condition1}	0.03
τ₁₁ _{subject_id.re1.block_number_scaled_by_reward_condition1}	0.01
ρ₀₁
ρ₀₁
ICC	0.00
N _{subject_id}	151
Observations	11267
Marginal R² / Conditional R²	0.111 / 0.113

Supplementary Figure: Generalization by trial, reward condition, and block number

Figure 2C: WSLS by age group

Supplementary Figure: WSLS by block number

Supplementary Figure: WSLS by block number and age group

Model: Category win-stay lose-shift

	WSLS
Predictors	Odds Ratios	CI
age scaled	1.0283	0.9915 – 1.0665
learning trial scaled	1.0028	0.9798 – 1.0262
reward condition1	1.7550	1.6906 – 1.8218
block number scaled	1.0467	1.0147 – 1.0799
age scaled × learning trial scaled	1.0084	0.9853 – 1.0321
age scaled × reward condition1	1.0777	1.0382 – 1.1187
learning trial scaled × reward condition1	1.1690	1.1422 – 1.1963
age scaled × block number scaled	0.9789	0.9489 – 1.0099
learning trial scaled × block number scaled	0.9845	0.9620 – 1.0076
reward condition1 × block number scaled	1.0770	1.0523 – 1.1022
age scaled × learning trial scaled × reward condition1	1.0186	0.9952 – 1.0425
(age scaled × learning trial scaled) × block number scaled	1.0111	0.9879 – 1.0349
(age scaled × reward condition1) × block number scaled	0.9966	0.9737 – 1.0200
(learning trial scaled × reward condition1) × block number scaled	0.9908	0.9681 – 1.0141
(age scaled × learning trial scaled × reward condition1) × block number scaled	0.9749	0.9525 – 0.9978
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.03
τ₁₁ _{subject_id.re1.reward_condition1}	0.03
τ₁₁ _{subject_id.re1.block_number_scaled}	0.02
ρ₀₁
ρ₀₁
ICC	0.01
N _{subject_id}	151
Observations	34390
Marginal R² / Conditional R²	0.097 / 0.105

Stats: WSLS in first 10 trials

reward_condition	mean_WSLS	se_WSLS
Category-Predictive	0.6693	0.01003
Exemplar-Predictive	0.5899	0.01064

Supplementary Model: Influence of prior category and exemplar rewards on choice

	choice
Predictors	Odds Ratios	CI
prior cat reward scaled	1.8918	1.7996 – 1.9886
prior stim reward scaled	4.0021	3.5792 – 4.4750
reward condition1	0.9662	0.9324 – 1.0011
learning trial scaled	0.8433	0.8137 – 0.8740
age scaled	0.9354	0.8718 – 1.0037
prior cat reward scaled × reward condition1	1.5922	1.5218 – 1.6659
prior stim reward scaled × reward condition1	1.1055	1.0358 – 1.1800
prior cat reward scaled × learning trial scaled	1.0757	1.0387 – 1.1140
prior stim reward scaled × learning trial scaled	1.0595	1.0050 – 1.1169
reward condition1 × learning trial scaled	0.9712	0.9473 – 0.9957
prior cat reward scaled × age scaled	1.0388	0.9883 – 1.0918
prior stim reward scaled × age scaled	1.3194	1.1807 – 1.4743
reward condition1 × age scaled	0.9863	0.9517 – 1.0222
learning trial scaled × age scaled	0.9764	0.9420 – 1.0120
(prior cat reward scaled × reward condition1) × learning trial scaled	1.1822	1.1388 – 1.2273
(prior stim reward scaled × reward condition1) × learning trial scaled	0.8995	0.8564 – 0.9449
(prior cat reward scaled × reward condition1) × age scaled	1.0558	1.0093 – 1.1045
(prior stim reward scaled × reward condition1) × age scaled	1.0297	0.9643 – 1.0995
(prior cat reward scaled × learning trial scaled) × age scaled	1.0301	0.9944 – 1.0670
(prior stim reward scaled × learning trial scaled) × age scaled	0.9847	0.9335 – 1.0386
(reward condition1 × learning trial scaled) × age scaled	1.0006	0.9758 – 1.0260
(prior cat reward scaled × reward condition1 × learning trial scaled) × age scaled	1.0441	1.0056 – 1.0842
(prior stim reward scaled × reward condition1 × learning trial scaled) × age scaled	0.9644	0.9174 – 1.0138
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.17
τ₁₁ _{subject_id.re1.prior_cat_reward_scaled}	0.05
τ₁₁ _{subject_id.re1.prior_stim_reward_scaled}	0.40
τ₁₁ _{subject_id.re1.reward_condition1}	0.03
τ₁₁ _{subject_id.re1.learning_trial_scaled}	0.03
τ₁₁ _{subject_id.re1.prior_cat_reward_scaled_by_reward_condition1}	0.03
τ₁₁ _{subject_id.re1.prior_stim_reward_scaled_by_reward_condition1}	0.09
τ₁₁ _{subject_id.re1.prior_cat_reward_scaled_by_learning_trial_scaled}	0.00
τ₁₁ _{subject_id.re1.prior_stim_reward_scaled_by_learning_trial_scaled}	0.02
τ₁₁ _{subject_id.re1.reward_condition1_by_learning_trial_scaled}	0.00
τ₁₁ _{subject_id.re1.prior_cat_reward_scaled_by_reward_condition1_by_learning_trial_scaled}	0.01
τ₁₁ _{subject_id.re1.prior_stim_reward_scaled_by_reward_condition1_by_learning_trial_scaled}	0.01
ρ₀₁
ρ₀₁
ICC	0.05
N _{subject_id}	151
Observations	45702
Marginal R² / Conditional R²	0.504 / 0.529

Supplementary Figure: Influence of prior category and exemplar rewards on choice

Memory

Overall descriptive memory stats

subject_id	mean_mem	se_mem
3718	0.8177	NA
3722	0.7917	NA
3768	0.75	NA
3770	0.6615	NA
3812	0.6702	NA
3816	0.776	NA
3817	0.6771	NA
3834	0.6667	NA
3835	0.7016	NA
3838	0.6878	NA
3841	0.776	NA
3844	0.7188	NA
3848	0.7407	NA
3853	0.7812	NA
3855	0.6562	NA
3856	0.7604	NA
3857	0.6979	NA
3861	0.8385	NA
3862	0.7135	NA
3871	0.5885	NA
3878	0.6875	NA
3883	0.776	NA
3898	0.7016	NA
3994	0.7604	NA
3998	0.8438	NA
3999	0.7083	NA
4003	0.724	NA
4007	0.6387	NA
4008	0.7812	NA
4011	0.8177	NA
4016	0.7812	NA
4022	0.7292	NA
4024	0.6719	NA
4028	0.6042	NA
4032	0.8385	NA
4036	0.6771	NA
4041	0.75	NA
4045	0.5885	NA
4050	0.7448	NA
4052	0.7552	NA
4062	0.7708	NA
4077	0.7083	NA
4087	0.6875	NA
4092	0.7135	NA
4097	0.5521	NA
4098	0.7708	NA
4284	0.7292	NA
4293	0.6875	NA
4294	0.7865	NA
4300	0.75	NA
4306	0.6823	NA
4487	0.6823	NA
4491	0.724	NA
4494	0.7865	NA
4495	0.8125	NA
4500	0.8281	NA
4506	0.8021	NA
4507	0.7448	NA
4508	0.8281	NA
4516	0.7031	NA
4521	0.7656	NA
4855	0.7487	NA
4857	0.7812	NA
5174	0.7135	NA
5175	0.625	NA
5178	0.7083	NA
5191	0.7604	NA
5193	0.776	NA
5433	0.7812	NA
5560	0.5604	NA
5565	0.7344	NA
5592	0.7865	NA
5626	0.7708	NA
5635	0.8281	NA
5639	0.6302	NA
5640	0.8542	NA
5641	0.8177	NA
5714	0.6667	NA
5719	0.6406	NA
5720	0.724	NA
5723	0.5104	NA
5757	0.7135	NA
5759	0.7344	NA
5809	0.7812	NA
5810	0.6094	NA
5811	0.776	NA
5813	0.6719	NA
5866	0.776	NA
5878	0.7344	NA
5884	0.7083	NA
5885	0.8542	NA
5887	0.7448	NA
5888	0.6283	NA
5889	0.8177	NA
5890	0.7656	NA
5938	0.6927	NA
6055	0.6302	NA
6130	0.6979	NA
6131	0.6719	NA
6132	0.7396	NA
6135	0.8542	NA
6153	0.6302	NA
6212	0.7031	NA
6217	0.7708	NA
6223	0.7448	NA
6256	0.6615	NA
6275	0.776	NA
6279	0.8333	NA
6280	0.8021	NA
6285	0.8115	NA
6286	0.6979	NA
6289	0.8125	NA
6292	0.7865	NA
6293	0.7188	NA
6294	0.7917	NA
6295	0.7344	NA
6380	0.6667	NA
6381	0.7016	NA
6407	0.6458	NA
6409	0.8281	NA
6410	0.7917	NA
6411	0.6458	NA
6414	0.7708	NA
6416	0.776	NA
6417	0.6615	NA
6460	0.651	NA
6461	0.6354	NA
6489	0.7812	NA
6490	0.849	NA
7056	0.7396	NA
7077	0.5521	NA
7083	0.6667	NA
7145	0.8177	NA
7147	0.6979	NA
7148	0.7292	NA
7196	0.8333	NA
7198	0.6387	NA
7199	0.7396	NA
7200	0.8281	NA
7240	0.6875	NA
7253	0.6354	NA
7579	0.4688	NA
7647	0.8542	NA
7653	0.7656	NA
7654	0.7292	NA
7695	0.5729	NA
7717	0.6771	NA
7731	0.8229	NA
7733	0.7917	NA
7909	0.6927	NA
8071	0.6406	NA

age_group	mean_mem	se_mem
Children	0.7122	0.01077
Adolescents	0.729	0.01024
Adults	0.741	0.01065

Memory delay stats

mean_delay	sd_delay	min_delay	max_delay
7.132	1.3	6	10

memory_delay	n
6	69
7	32
8	21
9	19
10	10

Supplementary Figure: AUC values by stimulus repetitions, block condition, age group

Model: AUC values by stimulus repetitions, block condition, age

	AUC
Predictors	Estimates	CI
age scaled	0.0147	0.0009 – 0.0285
reward condition1	-0.0091	-0.0135 – -0.0047
stim rep scaled	0.0432	0.0388 – 0.0475
age scaled × reward condition1	-0.0042	-0.0086 – 0.0002
age scaled × stim rep scaled	-0.0006	-0.0049 – 0.0038
reward condition1 × stim rep scaled	0.0011	-0.0033 – 0.0055
(age scaled × reward condition1) × stim rep scaled	0.0023	-0.0021 – 0.0067
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.60
N _{subject_id}	151
Observations	912
Marginal R² / Conditional R²	0.162 / 0.662

Figure 3A: AUC values by age group, memory specificity, block condition

foil_type	mean_auc	se_auc
category	0.8319	0.006013
exemplar	0.7118	0.005556

Model: AUCs by age, reward condition, memory specificity

	AUC
Predictors	Estimates	CI
age scaled	0.0159	0.0023 – 0.0294
reward condition1	-0.0084	-0.0132 – -0.0036
foil type1	0.0600	0.0552 – 0.0648
age scaled × reward condition1	-0.0042	-0.0090 – 0.0006
age scaled × foil type1	0.0021	-0.0027 – 0.0069
reward condition1 × foil type1	0.0013	-0.0035 – 0.0061
age scaled × reward condition1 × foil type1	0.0016	-0.0032 – 0.0063
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.63
N _{subject_id}	151
Observations	608
Marginal R² / Conditional R²	0.286 / 0.739

Model: AUCs by age, reward condition, foil type, memory delay

	AUC
Predictors	Estimates	CI
age scaled	0.0123	-0.0012 – 0.0258
reward condition1	-0.0083	-0.0131 – -0.0034
foil type1	0.0598	0.0549 – 0.0646
memory delay scaled	-0.0148	-0.0281 – -0.0014
age scaled × reward condition1	-0.0038	-0.0088 – 0.0011
age scaled × foil type1	0.0016	-0.0034 – 0.0065
reward condition1 × foil type1	0.0014	-0.0034 – 0.0063
age scaled × memory delay scaled	-0.0137	-0.0272 – -0.0002
reward condition1 × memory delay scaled	0.0021	-0.0028 – 0.0069
foil type1 × memory delay scaled	-0.0026	-0.0075 – 0.0023
age scaled × reward condition1 × foil type1	0.0019	-0.0030 – 0.0068
(age scaled × reward condition1) × memory delay scaled	0.0013	-0.0036 – 0.0063
(age scaled × foil type1) × memory delay scaled	-0.0020	-0.0069 – 0.0030
(reward condition1 × foil type1) × memory delay scaled	-0.0001	-0.0050 – 0.0048
(age scaled × reward condition1 × foil type1) × memory delay scaled	0.0021	-0.0028 – 0.0070
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.62
N _{subject_id}	151
Observations	604
Marginal R² / Conditional R²	0.312 / 0.738

Supplementary Figure: AUC values with delay

RL modeling

Choice weights

Figure: Choice weights histogram

Figure 2E: Choice weights boxplots

Presentation figure: Choice weights without age

Model: Choice weights by block condition and age

	est
Predictors	Estimates	CI
abstraction1	-0.4633	-0.5361 – -0.3905
reward condition1	0.2448	0.1720 – 0.3175
age scaled	0.1835	0.0839 – 0.2831
abstraction1 × reward condition1	0.3241	0.2513 – 0.3969
abstraction1 × age scaled	-0.0723	-0.1452 – 0.0005
reward condition1 × age scaled	0.0542	-0.0186 – 0.1271
(abstraction1 × reward condition1) × age scaled	0.0567	-0.0162 – 0.1295
Random Effects
σ²	0.83
τ₀₀ _{subject_id}	0.18
ICC	0.18
N _{subject_id}	151
Observations	604
Marginal R² / Conditional R²	0.296 / 0.422

Model: Exemplar choice weights across conditions

	est
Predictors	Estimates	CI
reward condition1	-0.0794	-0.1621 – 0.0034
Random Effects
σ²	0.53
τ₀₀ _{subject_id}	0.59
ICC	0.52
N _{subject_id}	151
Observations	302
Marginal R² / Conditional R²	0.006 / 0.526

Model: Category choice weights across conditions

	est
Predictors	Estimates	CI
reward condition1	0.5689	0.4688 – 0.6690
Random Effects
σ²	0.78
τ₀₀ _{subject_id}	0.20
ICC	0.20
N _{subject_id}	151
Observations	302
Marginal R² / Conditional R²	0.250 / 0.400

Supplementary Model: Relation between exemplar and category choice weights

	beta_e_scaled
Predictors	Estimates	CI
beta c scaled	-0.0555	-0.1753 – 0.0643
age scaled	0.2633	0.1146 – 0.4120
block condition1	-0.0414	-0.1421 – 0.0594
beta c scaled × age scaled	-0.0594	-0.1793 – 0.0605
beta c scaled × block condition1	-0.1260	-0.2325 – -0.0195
age scaled × block condition1	0.0458	-0.0568 – 0.1484
beta c scaled × age scaled × block condition1	-0.0000	-0.1079 – 0.1078
Random Effects
σ²	0.46
τ₀₀ _{subject_id}	0.48
ICC	0.51
N _{subject_id}	151
Observations	302
Marginal R² / Conditional R²	0.076 / 0.548

## 
## Call:
## lm(formula = beta_e_scaled ~ beta_c_scaled * age_scaled, data = beta_ests_wide_exemp_pred)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.5077 -0.5259  0.0725  0.5729  2.8088 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)               2.019e-05  7.690e-02   0.000   0.9998    
## beta_c_scaled             1.469e-01  7.715e-02   1.904   0.0589 .  
## age_scaled                3.138e-01  7.730e-02   4.059 7.98e-05 ***
## beta_c_scaled:age_scaled -9.041e-02  7.599e-02  -1.190   0.2361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9449 on 147 degrees of freedom
## Multiple R-squared:  0.125,  Adjusted R-squared:  0.1072 
## F-statistic: 7.001 on 3 and 147 DF,  p-value: 0.0001961

	beta_e_scaled
Predictors	Estimates	CI
beta c scaled	0.1469	-0.0056 – 0.2994
age scaled	0.3138	0.1610 – 0.4665
beta c scaled × age scaled	-0.0904	-0.2406 – 0.0598
Observations	151
R² / R² adjusted	0.125 / 0.107

## 
## Call:
## lm(formula = beta_e_scaled ~ beta_c_scaled * age_scaled, data = beta_ests_wide_cat_pred)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.77429 -0.64728  0.09172  0.69235  2.25603 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)   
## (Intercept)               0.01733    0.08263   0.210  0.83420   
## beta_c_scaled            -0.04539    0.08352  -0.543  0.58766   
## age_scaled                0.22259    0.08344   2.668  0.00849 **
## beta_c_scaled:age_scaled -0.07484    0.08586  -0.872  0.38482   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9855 on 147 degrees of freedom
## Multiple R-squared:  0.04813,    Adjusted R-squared:  0.0287 
## F-statistic: 2.477 on 3 and 147 DF,  p-value: 0.06364

Model: Relations between choice weights and points earned

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_c_c)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -279.190  -35.267    4.625   38.436  106.329 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  101.430      7.660  13.241  < 2e-16 ***
## est           38.762      4.837   8.013 2.99e-13 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 56.58 on 149 degrees of freedom
## Multiple R-squared:  0.3012, Adjusted R-squared:  0.2965 
## F-statistic: 64.21 on 1 and 149 DF,  p-value: 2.986e-13

	total_points
Predictors	Estimates	CI
est	38.7624	29.2036 – 48.3212
Observations	151
R² / R² adjusted	0.301 / 0.296

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_e_c)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -267.742  -34.803    7.474   43.234  123.277 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   133.74       8.64  15.480   <2e-16 ***
## est            10.84       4.37   2.482   0.0142 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 66.33 on 149 degrees of freedom
## Multiple R-squared:  0.03969,    Adjusted R-squared:  0.03324 
## F-statistic: 6.158 on 1 and 149 DF,  p-value: 0.01419

	total_points
Predictors	Estimates	CI
est	10.8435	2.2090 – 19.4780
Observations	151
R² / R² adjusted	0.040 / 0.033

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_c_e)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -324.49  -44.22    2.05   55.39  193.40 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  158.021      7.093   22.28   <2e-16 ***
## est           -6.648      6.924   -0.96    0.339    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 86.48 on 149 degrees of freedom
## Multiple R-squared:  0.006149,   Adjusted R-squared:  -0.0005209 
## F-statistic: 0.9219 on 1 and 149 DF,  p-value: 0.3385

	total_points
Predictors	Estimates	CI
est	-6.6479	-20.3292 – 7.0335
Observations	151
R² / R² adjusted	0.006 / -0.001

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_e_e)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -304.605  -36.510   -4.854   48.317  219.487 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   56.772     13.106   4.332 2.71e-05 ***
## est           58.972      6.908   8.537 1.47e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 71.08 on 149 degrees of freedom
## Multiple R-squared:  0.3285, Adjusted R-squared:  0.324 
## F-statistic: 72.88 on 1 and 149 DF,  p-value: 1.468e-14

	total_points
Predictors	Estimates	CI
est	58.9724	45.3227 – 72.6221
Observations	151
R² / R² adjusted	0.328 / 0.324

Figure 2D: Effect of choice weights on points earned

Relations between learning and memory

Model: Does the reward value of individual items relate to memory?

	mem_acc
Predictors	Odds Ratios	CI
age z	1.0752	0.9608 – 1.2033
reward condition1	0.9350	0.8881 – 0.9844
abs reward z	1.0180	0.9767 – 1.0610
reward sign1	0.9407	0.9000 – 0.9832
age z × reward condition1	0.9486	0.9011 – 0.9986
age z × abs reward z	0.9997	0.9594 – 1.0416
reward condition1 × abs reward z	0.9412	0.9031 – 0.9810
age z × reward sign1	0.9914	0.9486 – 1.0361
reward condition1 × reward sign1	0.9945	0.9549 – 1.0357
abs reward z × reward sign1	0.9861	0.9461 – 1.0279
(age z × reward condition1) × abs reward z	0.9358	0.8981 – 0.9751
age z × reward condition1 × reward sign1	0.9933	0.9539 – 1.0344
age z × abs reward z × reward sign1	1.0146	0.9736 – 1.0572
reward condition1 × abs reward z × reward sign1	0.9755	0.9358 – 1.0168
age z × reward condition1 × abs reward z × reward sign1	1.0175	0.9765 – 1.0603
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.43
τ₁₁ _{subject_id.re1.reward_condition1}	0.04
τ₁₁ _{subject_id.re1.reward_sign1}	0.01
ρ₀₁
ρ₀₁
ICC	0.12
N _{subject_id}	151
Observations	13669
Marginal R² / Conditional R²	0.008 / 0.122

Do points earned during learning relate to memory?

Model: AUC by points earned

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: AUC ~ age_scaled * points_scaled * abstraction * reward_condition +  
##     (1 | subject_id)
##    Data: data
## 
## REML criterion at convergence: -1249
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.4573 -0.5178  0.0325  0.6283  2.5841 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  subject_id (Intercept) 0.005858 0.07654 
##  Residual               0.003619 0.06016 
## Number of obs: 608, groups:  subject_id, 151
## 
## Fixed effects:
##                                                           Estimate Std. Error
## (Intercept)                                              7.710e-01  6.843e-03
## age_scaled                                               1.277e-02  6.865e-03
## points_scaled                                            8.960e-03  4.357e-03
## abstraction1                                             6.032e-02  2.607e-03
## reward_condition1                                       -6.419e-03  2.675e-03
## age_scaled:points_scaled                                -3.026e-04  4.321e-03
## age_scaled:abstraction1                                  4.972e-04  2.655e-03
## points_scaled:abstraction1                               5.044e-03  2.941e-03
## age_scaled:reward_condition1                            -2.624e-03  2.755e-03
## points_scaled:reward_condition1                         -3.825e-03  3.593e-03
## abstraction1:reward_condition1                          -1.082e-04  2.607e-03
## age_scaled:points_scaled:abstraction1                    1.693e-04  2.780e-03
## age_scaled:points_scaled:reward_condition1              -4.781e-03  3.312e-03
## age_scaled:abstraction1:reward_condition1               -9.863e-04  2.655e-03
## points_scaled:abstraction1:reward_condition1             6.957e-03  2.941e-03
## age_scaled:points_scaled:abstraction1:reward_condition1  4.803e-03  2.780e-03
##                                                                 df t value
## (Intercept)                                              1.532e+02 112.665
## age_scaled                                               1.554e+02   1.859
## points_scaled                                            5.791e+02   2.057
## abstraction1                                             4.379e+02  23.134
## reward_condition1                                        4.485e+02  -2.400
## age_scaled:points_scaled                                 5.898e+02  -0.070
## age_scaled:abstraction1                                  4.379e+02   0.187
## points_scaled:abstraction1                               4.379e+02   1.715
## age_scaled:reward_condition1                             4.531e+02  -0.953
## points_scaled:reward_condition1                          5.070e+02  -1.065
## abstraction1:reward_condition1                           4.379e+02  -0.041
## age_scaled:points_scaled:abstraction1                    4.379e+02   0.061
## age_scaled:points_scaled:reward_condition1               4.987e+02  -1.443
## age_scaled:abstraction1:reward_condition1                4.379e+02  -0.372
## points_scaled:abstraction1:reward_condition1             4.379e+02   2.366
## age_scaled:points_scaled:abstraction1:reward_condition1  4.379e+02   1.728
##                                                         Pr(>|t|)    
## (Intercept)                                               <2e-16 ***
## age_scaled                                                0.0649 .  
## points_scaled                                             0.0402 *  
## abstraction1                                              <2e-16 ***
## reward_condition1                                         0.0168 *  
## age_scaled:points_scaled                                  0.9442    
## age_scaled:abstraction1                                   0.8515    
## points_scaled:abstraction1                                0.0870 .  
## age_scaled:reward_condition1                              0.3413    
## points_scaled:reward_condition1                           0.2876    
## abstraction1:reward_condition1                            0.9669    
## age_scaled:points_scaled:abstraction1                     0.9515    
## age_scaled:points_scaled:reward_condition1                0.1496    
## age_scaled:abstraction1:reward_condition1                 0.7104    
## points_scaled:abstraction1:reward_condition1              0.0184 *  
## age_scaled:points_scaled:abstraction1:reward_condition1   0.0848 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

	AUC
Predictors	Estimates	CI
age scaled	0.0128	-0.0007 – 0.0262
points scaled	0.0090	0.0004 – 0.0175
abstraction1	0.0603	0.0552 – 0.0654
reward condition1	-0.0064	-0.0117 – -0.0012
age scaled × points scaled	-0.0003	-0.0088 – 0.0082
age scaled × abstraction1	0.0005	-0.0047 – 0.0057
points scaled × abstraction1	0.0050	-0.0007 – 0.0108
age scaled × reward condition1	-0.0026	-0.0080 – 0.0028
points scaled × reward condition1	-0.0038	-0.0109 – 0.0032
abstraction1 × reward condition1	-0.0001	-0.0052 – 0.0050
age scaled × points scaled × abstraction1	0.0002	-0.0053 – 0.0056
age scaled × points scaled × reward condition1	-0.0048	-0.0113 – 0.0017
age scaled × abstraction1 × reward condition1	-0.0010	-0.0062 – 0.0042
points scaled × abstraction1 × reward condition1	0.0070	0.0012 – 0.0127
age scaled × points scaled × abstraction1 × reward condition1	0.0048	-0.0007 – 0.0103
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.62
N _{subject_id}	151
Observations	608
Marginal R² / Conditional R²	0.303 / 0.734

Figure 3B: AUC by performance group and reward condition

Do choice weights relate to memory?

Model: AUC by age, exemplar choice weights, specificity, block condition

	AUC
Predictors	Estimates	CI
age scaled	0.0097	-0.0036 – 0.0230
beta scaled	0.0180	0.0087 – 0.0273
abstraction1	0.0610	0.0560 – 0.0659
reward condition1	-0.0052	-0.0103 – -0.0002
age scaled × beta scaled	0.0159	0.0051 – 0.0267
age scaled × abstraction1	0.0038	-0.0012 – 0.0088
beta scaled × abstraction1	-0.0044	-0.0098 – 0.0009
age scaled × reward condition1	-0.0003	-0.0054 – 0.0048
beta scaled × reward condition1	-0.0097	-0.0158 – -0.0035
abstraction1 × reward condition1	-0.0001	-0.0051 – 0.0048
age scaled × beta scaled × abstraction1	-0.0041	-0.0099 – 0.0018
age scaled × beta scaled × reward condition1	-0.0075	-0.0141 – -0.0009
age scaled × abstraction1 × reward condition1	0.0011	-0.0039 – 0.0061
beta scaled × abstraction1 × reward condition1	-0.0006	-0.0059 – 0.0048
age scaled × beta scaled × abstraction1 × reward condition1	0.0044	-0.0014 – 0.0102
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.62
N _{subject_id}	151
Observations	608
Marginal R² / Conditional R²	0.322 / 0.741

Figure 3C: AUC by exemplar choice weights - model effects

Model: AUC by age, category choice weights, specificity, block condition

	AUC
Predictors	Estimates	CI
age scaled	0.0196	0.0054 – 0.0337
beta scaled	0.0000	-0.0083 – 0.0084
abstraction1	0.0593	0.0536 – 0.0649
reward condition1	-0.0076	-0.0142 – -0.0010
age scaled × beta scaled	-0.0017	-0.0101 – 0.0066
age scaled × abstraction1	0.0025	-0.0033 – 0.0082
beta scaled × abstraction1	0.0070	0.0014 – 0.0126
age scaled × reward condition1	-0.0029	-0.0096 – 0.0039
beta scaled × reward condition1	0.0001	-0.0069 – 0.0071
abstraction1 × reward condition1	-0.0019	-0.0075 – 0.0038
age scaled × beta scaled × abstraction1	-0.0012	-0.0069 – 0.0045
age scaled × beta scaled × reward condition1	-0.0070	-0.0141 – 0.0001
age scaled × abstraction1 × reward condition1	0.0014	-0.0043 – 0.0072
beta scaled × abstraction1 × reward condition1	0.0022	-0.0035 – 0.0078
age scaled × beta scaled × abstraction1 × reward condition1	-0.0023	-0.0080 – 0.0034
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.64
N _{subject_id}	151
Observations	608
Marginal R² / Conditional R²	0.290 / 0.741

Figure 3C: AUC by category choice weights: model effects

Figure (for presentation): Category and exemplar memory by exemplar choice weights

Figure (for presentation): Category and exemplar memory by category choice weights

Relations between age and other model parameters

Model: Initial Q values by age

	Estimate	Std. Error	t value	Pr(>\|t\|)
(Intercept)	0.7336	0.09476	7.742	1.38e-12
age_scaled	-0.2009	0.09508	-2.113	0.03625

Fitting linear model: q_init ~ age_scaled
Observations	Residual Std. Error	\(R^2\)	Adjusted \(R^2\)
151	1.164	0.0291	0.02258

	q_init
Predictors	Estimates	CI
age scaled	-0.2009	-0.3888 – -0.0130
Observations	151
R² / R² adjusted	0.029 / 0.023

Supplementary Figure: Initial Q values by age

Model: Alpha values by age

	Estimate	Std. Error	t value	Pr(>\|t\|)
(Intercept)	-0.6771	0.07922	-8.547	1.39e-14
age_scaled	0.007934	0.07949	0.09982	0.9206

Fitting linear model: alpha ~ age_scaled
Observations	Residual Std. Error	\(R^2\)	Adjusted \(R^2\)
151	0.9735	6.686e-05	-0.006644

	alpha
Predictors	Estimates	CI
age scaled	0.0079	-0.1491 – 0.1650
Observations	151
R² / R² adjusted	0.000 / -0.007

Memory Specificity Analyses: Experiment 1

Kate Nussenbaum

6/13/24

Import and process data

Learning

Model: Correct responses by age, trial, block number, and block condition

Figure 2A: Correct response by block condition, stimulus repetition, and age group

Supplementary Figure: Correct response by block condition and block number

Figure 2B: Generalization by block condition, category repetition, age group

Model: Correct response to first appearance of each stimulus

Supplementary Figure: Generalization by trial, reward condition, and block number

Figure 2C: WSLS by age group

Supplementary Figure: WSLS by block number

Supplementary Figure: WSLS by block number and age group

Model: Category win-stay lose-shift

Stats: WSLS in first 10 trials

Supplementary Model: Influence of prior category and exemplar rewards on choice

Supplementary Figure: Influence of prior category and exemplar rewards on choice

Memory

Overall descriptive memory stats

Memory delay stats

Supplementary Figure: AUC values by stimulus repetitions, block condition, age group

Model: AUC values by stimulus repetitions, block condition, age

Figure 3A: AUC values by age group, memory specificity, block condition

Model: AUCs by age, reward condition, memory specificity

Model: AUCs by age, reward condition, foil type, memory delay

Supplementary Figure: AUC values with delay

RL modeling

Choice weights

Figure: Choice weights histogram

Figure 2E: Choice weights boxplots

Presentation figure: Choice weights without age

Model: Choice weights by block condition and age

Model: Exemplar choice weights across conditions

Model: Category choice weights across conditions

Supplementary Model: Relation between exemplar and category choice weights

Model: Relations between choice weights and points earned

Figure 2D: Effect of choice weights on points earned

Relations between learning and memory

Model: Does the reward value of individual items relate to memory?

Do points earned during learning relate to memory?

Model: AUC by points earned

Figure 3B: AUC by performance group and reward condition

Do choice weights relate to memory?

Model: AUC by age, exemplar choice weights, specificity, block condition

Figure 3C: AUC by exemplar choice weights - model effects

Model: AUC by age, category choice weights, specificity, block condition

Figure 3C: AUC by category choice weights: model effects

Figure (for presentation): Category and exemplar memory by exemplar choice weights

Figure (for presentation): Category and exemplar memory by category choice weights

Relations between age and other model parameters

Model: Initial Q values by age

Supplementary Figure: Initial Q values by age

Model: Alpha values by age